The gut microbiota modulates differential adenoma suppression by B6/J and B6/N genetic backgrounds in Apc Min mice Abstract Tumor multiplicity in the ApcMin (Min) mouse model of CRC is a classic quantitative trait that is subject to complex genetic and environmental factors, and therefore serves as an ideal platform to study modifiers of disease. While disparate inbred genetic backgrounds have well-characterized modifying effects on tumor multiplicity, it is unclear whether more closely related backgrounds such as C57BL/6J and C57BL6/N differentially modify the phenotype. Furthermore, it is unknown whether the complex gut microbiota (GM) influences the effects of these background strains. We assessed tumor multiplicity in F1 mice generated from the original Min colony from the McArdle Laboratory at the University of Wisconsin (C57BL/6JMlcr-ApcMin) crossed with either C57BL/6J or C57BL/6N wild-type mice. We also used complex microbiota targeted rederivation to rederive B6NB6JMF1-ApcMin embryos using surrogate dams harboring complex GMs from two different sources to determine the effects of complex GM. Both B6/J and B6/N backgrounds significantly repressed tumor multiplicity. However, the B6/N background conferred a stronger dominant suppressive effect than B6/J. Moreover, we observed that complex GM likely modulated B6/N-mediated adenoma repression such that two distinct communities conferred differential tumor multiplicity in isogenic B6NB6JMF1-ApcMin mice. Although we cannot rule out possible maternal effects of embryo transfer, we show that B6/J and B6/N have modifier effects on Min, and these effects are further altered by the complex GM. Foremost, strict attention to genetic background and environmental variables influencing the GM is critical to enhance reproducibility in models of complex disease traits.

Transposable element-mediated structural variation analysis in dog breeds using whole-genome sequencing Abstract Naturally occurring diseases in dogs provide an important animal model for studying human disease including cancer, heart disease, and autoimmune disorders. Transposable elements (TEs) make up ~ 31% of the dog (Canis lupus familiaris) genome and are one of main drivers to cause genomic variations and alter gene expression patterns of the host genes, which could result in genetic diseases. To detect structural variations (SVs), we conducted whole-genome sequencing of three different breeds, including Maltese, Poodle, and Yorkshire Terrier. Genomic SVs were detected and visualized using BreakDancer program. We identified a total of 2328 deletion SV events in the three breeds compared with the dog reference genome of Boxer. The majority of the genetic variants were found to be TE insertion polymorphism (1229) and the others were TE-mediated deletion (489), non-TE-mediated deletion (542), simple repeat-mediated deletion (32), and other indel (36). Among the TE insertion polymorphism, 286 elements were full-length LINE-1s (L1s). In addition, the 49 SV candidates located in the genic regions were experimentally verified and their polymorphic rates within each breed were examined using PCR assay. Polymorphism analysis of the genomic variants revealed that some of the variants exist polymorphic in the three dog breeds, suggesting that their SV events recently occurred in the dog genome. The findings suggest that TEs have contributed to the genomic variations among the three dog breeds of Maltese, Poodle, and Yorkshire Terrier. In addition, the polymorphic events between the dog breeds indicate that TEs were recently retrotransposed in the dog genome.

The dark genome and pleiotropy: challenges for precision medicine Abstract Surprisingly we remain ignorant of the function of the majority of genes in the human and mouse genomes. The dark genome is a major obstacle to the interpretation of the function of human genetic variation and its impact on disease. At the same time, pleiotropy, how individual variants influence multiple phenotypes, is key to understanding gene function and the role of genes and genetic networks in disease systems. Both understanding the genetics of disease and developing new therapeutic approaches and advances in precision medicine are all compromised by our limited knowledge of gene function and pleiotropic effects. Illuminating the dark genome and revealing pleiotropy across the genome requires a highly coordinated and international effort to acquire and analyse high-dimensional phenotype data from model organisms. We describe briefly how the International Mouse Phenotyping Consortium is addressing these challenges and the novel features of the pleiotropic landscape that are revealed by functional genomics programmes at genome-wide scale.

Exploring the dark genome: implications for precision medicine Abstract The increase in the number of both patients and healthcare practitioners who grew up using the Internet and computers (so-called “digital natives”) is likely to impact the practice of precision medicine, and requires novel platforms for data integration and mining, as well as contextualized information retrieval. The “Illuminating the Druggable Genome Knowledge Management Center” (IDG KMC) quantifies data availability from a wide range of chemical, biological, and clinical resources, and has developed platforms that can be used to navigate understudied proteins (the “dark genome”), and their potential contribution to specific pathologies. Using the “Target Importance and Novelty Explorer” (TIN-X) highlights the role of LRRC10 (a dark gene) in dilated cardiomyopathy. Combining mouse and human phenotype data leads to increased strength of evidence, which is discussed for four additional dark genes: SLX4IP and its role in glucose metabolism, the role of HSF2BP in coronary artery disease, the involvement of ELFN1 in attention-deficit hyperactivity disorder and the role of VPS13D in mouse neural tube development and its confirmed role in childhood onset movement disorders. The workflow and tools described here are aimed at guiding further experimental research, particularly within the context of precision medicine.

Liver size and lipid content differences between BALB/c and BALB/cJ mice on a high-fat diet are due, in part, to Zhx2 Abstract BALB/cJ mice exhibit considerable phenotypic differences with other BALB/c substrains. Some of these traits involve the liver, including persistent postnatal expression of genes that are normally expressed only in the fetal liver and reduced expression of major urinary proteins. These traits are due to a mutation that dramatically reduces expression of the gene encoding the transcription factor Zinc fingers and homeoboxes 2 (Zhx2). BALB/cJ mice also exhibit reduced serum lipid levels and resistance to atherosclerosis compared to other mouse strains when placed on a high-fat diet. This trait is also due, at least in part, to the Zhx2 mutation. Microarray analysis identified many genes affecting lipid homeostasis, including Lipoprotein lipase, that are dysregulated in BALB/cJ liver. This led us to investigate whether hepatic lipid levels would be different between BALB/cJ and BALB/c mice when placed on a normal chow or a high-fat chow diet. On the high-fat chow, BALB/cJ mice had increased weight gain, increased liver:body weight ratio, elevated hepatic lipid accumulation and markers of liver damage when compared to BALB/c mice. These traits in BALB/cJ mice were only partially reversed by a hepatocyte-specific Zhx2 transgene. These data indicate that Zhx2 reduces liver lipid levels and is hepatoprotective in mice on a high-fat diet, but the partial rescue by the Zhx2 transgene suggests a contribution by both parenchymal and non-parenchymal cells. A model to account for the cardiovascular and liver phenotype in mice with reduced Zhx2 levels is provided.

Uses for humanised mouse models in precision medicine for neurodegenerative disease Abstract Neurodegenerative disease encompasses a wide range of disorders afflicting the central and peripheral nervous systems and is a major unmet biomedical need of our time. There are very limited treatments, and no cures, for most of these diseases, including Alzheimer’s Disease, Parkinson's Disease, Huntington Disease, and Motor Neuron Diseases. Mouse and other animal models provide hope by analysing them to understand pathogenic mechanisms, to identify drug targets, and to develop gene therapies and stem cell therapies. However, despite many decades of research, virtually no new treatments have reached the clinic. Increasingly, it is apparent that human heterogeneity within clinically defined neurodegenerative disorders, and between patients with the same genetic mutations, significantly impacts disease presentation and, potentially, therapeutic efficacy. Therefore, stratifying patients according to genetics, lifestyle, disease presentation, ethnicity, and other parameters may hold the key to bringing effective therapies from the bench to the clinic. Here, we discuss genetic and cellular humanised mouse models, and how they help in defining the genetic and environmental parameters associated with neurodegenerative disease, and so help in developing effective precision medicine strategies for future healthcare.

Amplification of lncRNA PVT1 promotes ovarian cancer proliferation by binding to miR-140 Abstract Gene deletion or gene amplification acts as a driving factor of onset, progress, and metastasis in various cancers, including ovarian cancers. By mining the whole genome data of ovarian cancer patients, we identify the long noncoding RNA PVT1 as the most amplified gene. Knockdown of PVT1 was then achieved using a shRNA in two ovarian cancer cell lines, and cell viability was determined by trypan blue exclusion assay, cell metabolism by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay, and cell cycle alteration by propidium iodide cell cycle analysis. Potential targeting microRNAs were predicted with starBase v2.0, and direct binding of miR-140 on PVT1 was confirmed by luciferase reporter assay and microRNA pull-down assay. Evolutionary conserved transcription factor-binding site was predicted via rVista 2.0. Our results show that PVT1 was the most amplified gene in ovarian cancer patients, and it was highly correlated with poor survival outcomes. Knockdown of PVT1 caused decreased cell viability, metabolic activity, and smaller proportion of S-phase cells. PVT1 directly bound to miR-140 and acted as a microRNA sponge, while transcription of PVT1 was regulated by the transcription factor FOXO4. In conclusion, viability, metabolism, and cell cycle of ovarian cancers are regulated by the FOXO4/PVT1/miR-140 signaling pathway.

Closing the ‘phenotype gap’ in precision medicine: improving what we measure to understand complex disease mechanisms Abstract The central concept underlying precision medicine is a mechanistic understanding of each disease and its response to therapy sufficient to direct a specific intervention. To execute on this vision requires parsing incompletely defined disease syndromes into discrete mechanistic subsets and developing interventions to precisely address each of these etiologically distinct entities. This will require substantial adjustment of traditional paradigms which have tended to aggregate high-level phenotypes with very different etiologies. In the current environment, where diagnoses are not mechanistic, drug development has become so expensive that it is now impractical to imagine the cost-effective creation of new interventions for many prevalent chronic conditions. The vision of precision medicine also argues for a much more seamless integration of research and development with clinical care, where shared taxonomies will enable every clinical interaction to inform our collective understanding of disease mechanisms and drug responses. Ideally, this would be executed in ways that drive real-time and real-world discovery, innovation, translation, and implementation. Only in oncology, where at least some of the biology is accessible through surgical excision of the diseased tissue or liquid biopsy, has “co-clinical” modeling proven feasible. In most common germline disorders, while genetics often reveal the causal mutations, there still remain substantial barriers to efficient disease modeling. Aggregation of similar disorders under single diagnostic labels has directly contributed to the paucity of etiologic and mechanistic understanding by directly reducing the resolution of any subsequent studies. Existing clinical phenotypes are typically anatomic, physiologic, or histologic, and result in a substantial mismatch in information content between the phenomes in humans or in animal ‘models’ and the variation in the genome. This lack of one-to-one mapping of discrete mechanisms between disease and animal models causes a failure of translation and is one form of ‘phenotype gap.’ In this review, we will focus on the origins of the phenotyping deficit and approaches that may be considered to bridge the gap, creating shared taxonomies between human diseases and relevant models, using cardiovascular examples.

Precision medicine and Mammalian Genome

New models for human disease from the International Mouse Phenotyping Consortium Abstract The International Mouse Phenotyping Consortium (IMPC) continues to expand the catalogue of mammalian gene function by conducting genome and phenome-wide phenotyping on knockout mouse lines. The extensive and standardized phenotype screens allow the identification of new potential models for human disease through cross-species comparison by computing the similarity between the phenotypes observed in the mutant mice and the human phenotypes associated to their orthologous loci in Mendelian disease. Here, we present an update on the novel disease models available from the most recent data release (DR10.0), with 5861 mouse genes fully or partially phenotyped and a total number of 69,982 phenotype calls reported. With approximately one-third of human Mendelian genes with orthologous null mouse phenotypes described, the range of available models relevant for human diseases keeps increasing. Among the breadth of new data, we identify previously uncharacterized disease genes in the mouse and additional phenotypes for genes with existing mutant lines mimicking the associated disorder. The automated and unbiased discovery of relevant models for all types of rare diseases implemented by the IMPC constitutes a powerful tool for human genetics and precision medicine.